Assessment of imaging risks for recurrence after stereotactic radiosurgery for brain metastases (IRRaS-BM).

BACKGROUND: The identification of viable tumors and radiation necrosis after stereotactic radiosurgery (SRS) is crucial for patient management. Tumor habitat analysis involving the grouping of similar voxels can identify subregions that share common biology and enable the depiction of areas of tumor recurrence and treatment-induced change. This study aims to validate an imaging biomarker for tumor recurrence after SRS for brain metastasis by conducting tumor habitat analysis using multi-parametric MRI. METHODS: In this prospective study (NCT05868928), patients with brain metastases will undergo multi-parametric MRI before SRS, and then follow-up MRIs will be conducted every 3 months until 24 months after SRS. The multi-parametric MRI protocol will include T2-weighted and contrast-enhanced T1-weighted imaging, diffusion-weighted imaging, and dynamic susceptibility contrast imaging. Using k-means voxel-wise clustering, this study will define three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) on T1- and T2-weighted images and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable) on apparent diffusion coefficient maps and cerebral blood volume maps. Using RANO-BM criteria as the reference standard, via Cox proportional hazards analysis, the study will prospectively evaluate associations between parameters of the tumor habitats and the time to recurrence. The DICE similarity coefficients between the recurrence site and tumor habitats will be calculated. DISCUSSION: The tumor habitat analysis will provide an objective and reliable measure for assessing tumor recurrence from brain metastasis following SRS. By identifying subregions for local recurrence, our study could guide the next therapeutic targets for patients after SRS. TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov (NCT05868928).

Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation.

OBJECTIVES: The Image Biomarker Standardization Initiative has helped improve the computational reproducibility of MRI radiomics features. Nonetheless, the MRI sequences and features with high imaging reproducibility are yet to be established. To determine reproducible multiparametric MRI radiomics features across test-retest, multi-scanner, and computational reproducibility comparisons, and to evaluate their clinical value in brain tumor diagnosis. METHODS: To assess reproducibility, T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI) were acquired from three 3-T MRI scanners using standardized phantom, and radiomics features were extracted using two computational algorithms. Reproducible radiomics features were selected when the concordance correlation coefficient value above 0.9 across multiple sessions, scanners, and computational algorithms. Random forest classifiers were trained with reproducible features (n = 117) and validated in a clinical cohort (n = 50) to evaluate whether features with high reproducibility improved the differentiation of glioblastoma from primary central nervous system lymphomas (PCNSLs). RESULTS: Radiomics features from T2WI demonstrated higher repeatability (65-94%) than those from DWI (38-48%) or T1WI (2-92%). Across test-retest, multi-scanner, and computational comparisons, T2WI provided 41 reproducible features, DWI provided six, and T1WI provided two. The performance of the classification model with reproducible features was higher than that using non-reproducible features in both training set (AUC, 0.916 vs. 0.877) and validation set (AUC, 0.957 vs. 0.869). CONCLUSION: Radiomics features with high reproducibility across multiple sessions, scanners, and computational algorithms were identified, and they showed higher diagnostic performance than non-reproducible radiomics features in the differentiation of glioblastoma from PCNSL. CLINICAL RELEVANCE STATEMENT: By identifying the radiomics features showing higher multi-machine reproducibility, our results also demonstrated higher radiomics diagnostic performance in the differentiation of glioblastoma from PCNSL, paving the way for further research designs and clinical application in neuro-oncology. KEY POINTS: • Highly reproducible radiomics features across multiple sessions, scanners, and computational algorithms were identified using phantom and applied to clinical diagnosis. • Radiomics features from T2-weighted imaging were more reproducible than those from T1-weighted and diffusion-weighted imaging. • Radiomics features with good reproducibility had better diagnostic performance for brain tumors than features with poor reproducibility.

Exploring metabolic effects of dipeptide feed media on CHO cell cultures by in silico model-guided flux analysis.

There is a growing interest in perfusion or continuous processes to achieve higher productivity of biopharmaceuticals in mammalian cell culture, specifically Chinese hamster ovary (CHO) cells, towards advanced biomanufacturing. These intensified bioprocesses highly require concentrated feed media in order to counteract their dilution effects. However, designing such condensed media formulation poses several challenges, particularly regarding the stability and solubility of specific amino acids. To address the difficulty and complexity in relevant media development, the biopharmaceutical industry has recently suggested forming dipeptides by combining one from problematic amino acids with selected pairs to compensate for limitations. In this study, we combined one of the lead amino acids, L-tyrosine, which is known for its poor solubility in water due to its aromatic ring and hydroxyl group, with glycine as the partner, thus forming glycyl-L-tyrosine (GY) dipeptide. Subsequently, we investigated the utilization of GY dipeptide during fed-batch cultures of IgG-producing CHO cells, by changing its concentrations (0.125 × , 0.25 × , 0.5 × , 1.0 × , and 2.0 ×). Multivariate statistical analysis of culture profiles was then conducted to identify and correlate the most significant nutrients with the production, followed by in silico model-guided analysis to systematically evaluate their effects on the culture performance, and elucidate metabolic states and cellular behaviors. As such, it allowed us to explain how the cells can more efficiently utilize GY dipeptide with respect to the balance of cofactor regeneration and energy distribution for the required biomass and protein synthesis. For example, our analysis results uncovered specific amino acids (Asn and Gln) and the 0.5 × GY dipeptide in the feed medium synergistically alleviated the metabolic bottleneck, resulting in enhanced IgG titer and productivity. In the validation experiments, we tested and observed that lower levels of Asn and Gln led to decreased secretion of toxic metabolites, enhanced longevity, and elevated specific cell growth and titer. KEY POINTS: • Explored the optimal Tyr dipeptide for the enhanced CHO cell culture performance • Systematically analyzed effects of dipeptide media by model-guided approach • Uncovered synergistic metabolic utilization of amino acids with dipeptide.

Establishment of canine mammary gland tumor cell lines harboring PI3K/Akt activation as a therapeutic target.

Canine mammary gland tumors (MGT) have a poor prognosis in intact female canines, posing a clinical challenge. This study aimed to establish novel canine mammary cancer cell lines from primary tumors and characterize their cellular and molecular features to find potential therapeutic drugs. The MGT cell lines demonstrated rapid cell proliferation and colony formation in an anchorage-independent manner. Vimentin and α-SMA levels were significantly elevated in MGT cell lines compared to normal canine kidney (MDCK) cells, while CDH1 expression was either significantly lower or not detected at all, based on quantitative real-time PCR (qRT-PCR) analysis. Functional annotation and enrichment analysis revealed that epithelial-mesenchymal transition (EMT) phenotypes and tumor-associated pathways, particularly the PI3K/Akt signaling pathway, were upregulated in MGT cells. BYL719 (Alpelisib), a PI3K inhibitor, was also examined for cytotoxicity on the MGT cell lines. The results show that BYL719 can significantly inhibit the proliferation of MGT cell lines in vitro. Overall, our findings suggest that the MGT cell lines may be valuable for future studies on the development, progression, metastasis, and management of tumors.

Recombinant expression and tryptophan-assisted analysis of human sweet taste receptor T1R3's extracellular domain in sweetener interaction studies.

The human palate can discern multiple tastes; however, it predominantly perceives five fundamental flavors: sweetness, saltiness, sourness, bitterness, and umami. Sweetness is primarily mediated through the sweet taste receptor, a membrane-bound heterodimeric structure comprising T1R2-T1R3. However, unraveling the structural and mechanistic intricacies of the sweet taste receptor has proven challenging. This study aimed to address this knowledge gap by expressing an extracellular N-terminal domain encompassing the cysteine-rich domain of human hT1R3 (hT1R3-TMD) in Escherichia coli. The expressed protein was obtained as inclusion bodies, purified by metal affinity chromatography, and refolded using the dilution-refolding method. Through rigorous analysis, we confirmed the successful refolding of hT1R3-TMD and elucidated its structural characteristics using circular dichroism spectroscopy. Notably, the refolded protein was found to exist as either a monomer or a dimer, depending on its concentration. A tryptophan fluorescence quenching assay revealed that the dissociation constants for sucrose, sucralose, and brazzein were >9500 µM, 2380 µM and 14.3 µM, respectively. Our findings highlight the utility of this E. coli expression system for producing functional hT1R3-TMD for investigations and demonstrate the efficacy of the tryptophan fluorescence quenching assay in revealing complex interactions between sweet taste receptors and various sweeteners.

Data-driven prediction models for forecasting multistep ahead profiles of mammalian cell culture toward bioprocess digital twins.

Recently, the advancement in process analytical technology and artificial intelligence (AI) has enabled the generation of enormous culture data sets from biomanufacturing processes that produce various recombinant therapeutic proteins (RTPs), such as monoclonal antibodies (mAbs). Thus, now it is very important to exploit them for the enhanced reliability, efficiency, and consistency of the RTP-producing culture processes and for the reduced incipient or abrupt faults. It is achievable by AI-based data-driven models (DDMs), which allow us to correlate biological and process conditions and cell culture states. In this work, we provide practical guidelines for choosing the best combination of model elements to design and implement successful DDMs for given hypothetical in-line data sets during mAb-producing Chinese hamster ovary cell culture, as such enabling us to forecast dynamic behaviors of culture performance such as viable cell density, mAb titer as well as glucose, lactate and ammonia concentrations. To do so, we created DDMs that balance computational load with model accuracy and reliability by identifying the best combination of multistep ahead forecasting strategies, input features, and AI algorithms, which is potentially applicable to implementation of interactive DDM within bioprocess digital twins. We believe this systematic study can help bioprocess engineers start developing predictive DDMs with their own data sets and learn how their cell cultures behave in near future, thereby rendering proactive decision possible.

Multiple arterial-phase MRI with gadoxetic acid improves diagnosis of hepatocellular carcinoma ≤3.0 cm.

BACKGROUND AND AIMS: Multiple arterial-phase magnetic resonance imaging (MA-MRI) was introduced to overcome the limitations of gadoxetic acid-enhanced MRI, but its clinical impacts on hepatocellular carcinoma (HCC) diagnosis have not been well assessed. We investigated whether MA-MRI with gadoxetic acid could improve the diagnosis of HCC ≤3.0 cm in comparison with single arterial-phase MRI (SA-MRI). METHODS: This retrospective study included 397 patients from two tertiary institutions who underwent gadoxetic acid-enhanced MRI (243 patients with 271 lesions in cohort-1 underwent SA-MRI, and 154 patients with 166 lesions in cohort-2 underwent MA-MRI). The patients had 437 hepatic lesions ≤3.0 cm with pathologic confirmation. The arterial-phase image quality and diagnostic performance of SA-MRI and MA-MRI were analysed and compared. To minimize the effects of selection bias because of potential confounding between the two groups, propensity score-matching was additionally performed. RESULTS: MA-MRI showed a significantly higher percentage of optimal arterial-phase timing (94.2% vs. 74.5%, p < .001) and lower incidence of inadequate examinations (1.3% vs. 5.8%, p = .034) than SA-MRI. MA-MRI had a significantly higher non-rim arterial-phase hyperenhancement (APHE) detection rate (94.9% vs. 85.5%, p = .005) and sensitivity for diagnosing HCC (87.4% vs. 70.0%, p < .001) than SA-MRI, but no significant difference in specificity (92.9% vs. 93.1%, p = .966). In 123 pairs of propensity score-matched patients, MA-MRI had significantly higher sensitivity (89.1% vs. 74.5%, p = .006) than SA-MRI with equal specificity (92.3% vs. 92.3%, p > .999). CONCLUSIONS: Compared with SA-MRI, MA-MRI with gadoxetic acid can detect more non-rim APHE and significantly improve sensitivity for diagnosing HCC ≤3.0 cm, without a significant decrease in specificity.

Reducing false positives in deep learning-based brain metastasis detection by using both gradient-echo and spin-echo contrast-enhanced MRI: validation in a multi-center diagnostic cohort.

OBJECTIVES: To develop a deep learning (DL) for detection of brain metastasis (BM) that incorporates both gradient- and turbo spin-echo contrast-enhanced MRI (dual-enhanced DL) and evaluate it in a clinical cohort in comparison with human readers and DL using gradient-echo-based imaging only (GRE DL). MATERIALS AND METHODS: DL detection was developed using data from 200 patients with BM (training set) and tested in 62 (internal) and 48 (external) consecutive patients who underwent stereotactic radiosurgery and diagnostic dual-enhanced imaging (dual-enhanced DL) and later guide GRE imaging (GRE DL). The detection sensitivity and positive predictive value (PPV) were compared between two DLs. Two neuroradiologists independently analyzed BM and reference standards for BM were separately drawn by another neuroradiologist. The relative differences (RDs) from the reference standard BM numbers were compared between the DLs and neuroradiologists. RESULTS: Sensitivity was similar between GRE DL (93%, 95% confidence interval [CI]: 90-96%) and dual-enhanced DL (92% [89-94%]). The PPV of the dual-enhanced DL was higher (89% [86-92%], p < .001) than that of GRE DL (76%, [72-80%]). GRE DL significantly overestimated the number of metastases (false positives; RD: 0.05, 95% CI: 0.00-0.58) compared with neuroradiologists (RD: 0.00, 95% CI: - 0.28, 0.15, p < .001), whereas dual-enhanced DL (RD: 0.00, 95% CI: 0.00-0.15) did not show a statistically significant difference from neuroradiologists (RD: 0.00, 95% CI: - 0.20-0.10, p = .913). CONCLUSION: The dual-enhanced DL showed improved detection of BM and reduced overestimation compared with GRE DL, achieving similar performance to neuroradiologists. CLINICAL RELEVANCE STATEMENT: The use of deep learning-based brain metastasis detection with turbo spin-echo imaging reduces false positive detections, aiding in the guidance of stereotactic radiosurgery when gradient-echo imaging alone is employed. KEY POINTS: •Deep learning for brain metastasis detection improved by using both gradient- and turbo spin-echo contrast-enhanced MRI (dual-enhanced deep learning). •Dual-enhanced deep learning increased true positive detections and reduced overestimation. •Dual-enhanced deep learning achieved similar performance to neuroradiologists for brain metastasis counts.

Impact of lesion size on reproducibility of quantitative measurement and radiomic features in vessel wall MRI.

OBJECTIVES: To investigate reproducibility of quantitative measurement and radiomic features in vessel wall MRI (VW-MRI), evaluate the impact of lesion size, and identify reproducible radiomic features. METHODS: This retrospective, single-center study included 251 patients (mean age, 53 ± 12 years; 128 women) with atherosclerosis, dissection, aneurysm, moyamoya disease, and vasculitis of the intracranial arteries who underwent three-dimensional turbo spin echo T1-weighted image. Lesion thickness, volume, and signal intensity were measured, and 157 radiomic features were extracted. Intra-observer reproducibility of quantitative measurement and radiomic features was evaluated by calculating the concordance correlation coefficient (CCC) and proportion of radiomic features above the predefined CCC. The reproducibility of quantitative measurement and radiomic features according to lesion size (binary comparison and stratification into 5 and 18 groups) was evaluated. RESULTS: There was an overall serial increase in CCC for thickness measurement when stratified by lesion thickness and volume. There was an overall serial increase in the median CCC for radiomic features and proportion of radiomic features with CCC > 0.85 when stratified by lesion thickness and volume. Reproducibility of radiomic features was higher in the lesions with thickness ≥ 2.5 mm (median CCC, 0.97 vs. 0.89, p < .001; proportion with CCC > 0.85, 88.5% vs. 59.6%, p < .001) and volume ≥ 50 mm3 (median CCC, 0.97 vs. 0.88, p < .001; proportion with CCC > 0.85, 90.4% vs. 59.0%, p < .001). Intensity-based statistical features remained most reproducible in the thinnest and smallest lesions. CONCLUSIONS: Intra-observer reproducibility of thickness measurement and radiomic features was affected by lesion size in VW-MRI although intensity-based statistical features remained most reproducible. KEY POINTS: • There was an overall serial increase in CCC for thickness measurement when stratified by lesion size. • There was an overall serial increase in the median CCC for radiomic features and proportion of radiomic features with CCC > 0.85 when stratified by lesion size. • Intensity-based statistical features remained most reproducible in the thinnest and smallest lesions.

Defining subventricular zone involvement to predict the survival of patients in isocitrate dehydrogenase-wild type glioblastoma: validation in a prospective registry.

OBJECTIVES: The prognostic value of subventricular zone distance (SVD) is unclear because of different definitions and lack of evaluation of clinical survival models. The aim of this study was to define SVD and evaluate its prognostic value in a survival nomogram for glioblastoma. METHODS: This retrospective study included 158 (SVD biomarker) from historical glioblastoma patients and 187 (survival modeling) with IDH-wild type glioblastoma from a prospective registry (NCT02619890). SVD was assessed by two radiologists: definition 1, the distance between the tumor edge to subventricular zone (SVZ); definition 2, the distance between the tumor centroid to SVZ; definition 3, enhancement at the ventricular wall. The associations between SVD and overall survival (OS) were evaluated using multivariable Cox proportional hazards regression analysis. Performance of an updated SVD survival model was compared with that of the Radiation Therapy Oncology Group (RTOG) 0525 nomogram. RESULTS: SVD according to both definition 1 (hazard ratio [HR]: 0.97, 95% CI: 0.94-0.99; p = .011) and definition 2 (HR: 0.96, 0.94-0.98, p < .001) was adversely associated with OS. Definition 1 was adversely associated with PFS (HR: 0.96, 0.94-0.99, p = .008) and showed the highest reproducibility (intraclass correlation coefficient, 0.90). The SVD-updated model showed similar to better performance than the RTOG model for predicting OS of up to 3 years (AUC: 0.735-0.738 vs. 0.687-0.708), with higher time-dependent specificity for 1-year (89.9% vs. 70.6%) and 3-year OS (93.3% vs. 80.0%). CONCLUSION: SVZ distance is an independent adverse prognostic factor in patients with IDH-wild type glioblastoma. Updating the survival model with SVZ provides better time-dependent specificity and reproducibility. KEY POINTS: • Subventricular zone distance (SVD) measurement from tumor edge showed high reproducibility. • Longer SVD was independently associated with longer overall survival. • Adding SVD improved time-dependent specificity for survival model in a prospective registry.

Diagnostic performance of synthetic relaxometry for predicting neurodevelopmental outcomes in premature infants: a feasibility study.

OBJECTIVES: To investigate the predictability of synthetic relaxometry for neurodevelopmental outcomes in premature infants and to evaluate whether a combination of relaxation times with clinical variables or qualitative MRI abnormalities improves the predictive performance. METHODS: This retrospective study included 33 premature infants scanned with synthetic MRI near or at term equivalent age. Based on neurodevelopmental assessments at 18-24 months of corrected age, infants were classified into two groups (no/mild disability [n = 23] vs. moderate/severe disability [n = 10]). Clinical and MRI characteristics associated with moderate/severe disability were explored, and combined models incorporating independent predictors were established. Ultimately, the predictability of relaxation times, clinical variables, MRI findings, and a combination of the two were evaluated and compared. The models were internally validated using bootstrap resampling. RESULTS: Prolonged T1-frontal/parietal and T2-parietal periventricular white matter (PVWM), moderate-to-severe white matter abnormality, and bronchopulmonary dysplasia were significantly associated with moderate/severe disability. The overall predictive performance of each T1-frontal/-parietal PVWM model was comparable to that of individual MRI finding and clinical models (AUC = 0.71 and 0.76 vs. 0.73 vs. 0.83, respectively; p > 0.27). The combination of clinical variables and T1-parietal PVWM achieved an AUC of 0.94, sensitivity of 90%, and specificity of 91.3%, outperforming the clinical model alone (p = 0.049). The combination of MRI finding and T1-frontal PVWM yielded AUC of 0.86, marginally outperforming the MRI finding model (p = 0.09). Bootstrap resampling showed that the models were valid. CONCLUSIONS: It is feasible to predict adverse outcomes in premature infants by using early synthetic relaxometry. Combining relaxation time with clinical variables or MRI finding improved prediction. CLINICAL RELEVANCE STATEMENT: Synthetic relaxometry performed during the neonatal period may serve as a biomarker for predicting adverse neurodevelopmental outcomes in premature infants. KEY POINTS: • Synthetic relaxometry based on T1 relaxation time of parietal periventricular white matter showed acceptable performance in predicting adverse outcome with an AUC of 0.76 and an accuracy of 78.8%. • The combination of relaxation time with clinical variables and/or structural MRI abnormalities improved predictive performance of adverse outcomes. • Synthetic relaxometry performed during the neonatal period helps predict adverse neurodevelopmental outcome in premature infants.

Functional significance of serine 13 in the active site of glutathione S-transferase F3 from Oryza sativa.

Plant glutathione S-transferase (GST, EC 2.5.1.18) is an enzyme that detoxifies various electrophilic compounds including herbicides and organic pollutants by catalyzing the formation of conjugates with reduced glutathione (GSH). Although the structure and function of the GST subunits in rice, an important food in Asia, are not well understood, they are crucial for herbicide development. To investigate the role of active site residues in rice Phi-class GSTF3 (OsGSTF3), evolutionarily conserved serine residues were replaced with alanine using site-directed mutagenesis to obtain the mutants S13A, S38A, S69A, and S169A. These four mutants were expressed in Escherichia coli and purified to electrophoretic homogeneity using immobilized GSH affinity chromatography. Mutation of Ser13 to Ala resulted in substantial reductions in specific activities and kcat/Km values for the GSH-[1-chloro-2,4-dinitrobenzene (CDNB)] conjugation reaction. In contrast, mutations of Ser38, Ser69, and Ser169 to Ala had little effect on the activities and kinetic parameters. Additionally, the mutation of Ser13 to Ala significantly affected the KmGSH and I50 values of S-hexylglutathione and S-(2,4-dinitrophenyl)glutathione, which compete with GSH and the product of GSH-CDNB conjugation, respectively. A pH-log (kcat/KmCDNB) plot was used to estimate the pKa value of GSH in the enzyme-GSH complex of the wild-type enzyme, which was approximately 6.9. However, the pKa value of GSH in the enzyme-GSH complex of the S13A mutant was approximately 8.7, which was about 1.8 pK units higher than that of the wild-type enzyme. OsGSTF3 was also crystallized for crystallographic study, and the structure analyses revealed that Ser13 is located in the active site and that its side chain is in close proximity to the thiol group of glutathione bound in the enzyme. Based on these substitution effects on kinetic parameters, the dependence of kinetic parameters on the pH and 3-dimensional structure, it was suggested that Ser13 in rice OsGSTF3 is the residue responsible for catalytic activity by lowering the pKa of GSH in the enzyme-GSH complex and enhancing the nucleophilicity of the GSH thiol in the active site.

Robotic versus laparoscopic distal pancreatectomy for pancreatic ductal adenocarcinoma: A propensity score-matched analysis.

BACKGROUND: Minimally invasive surgery is becoming increasingly popular in the field of pancreatic surgery. However, there are few studies of robotic distal pancreatectomy (RDP) for pancreatic ductal adenocarcinoma (PDAC). This study aimed to investigate the efficacy and feasibility of RDP for PDAC. METHODS: Patients who underwent RDP or laparoscopic distal pancreatectomy (LDP) for PDAC between January 2015 and September 2020 were reviewed. Propensity score matching analyses were performed. RESULTS: Of the 335 patients included in the study, 24 underwent RDP and 311 underwent LDP. A total of 21 RDP patients were matched 1:1 with LDP patients. RDP was associated with longer operative time (209.7 vs. 163.2 min; P = 0.003), lower open conversion rate (0% vs. 4.8%; P < 0.001), higher cost (15 722 vs. 12 699 dollars; P = 0.003), and a higher rate of achievement of an R0 resection margin (90.5% vs. 61.9%; P = 0.042). However, postoperative pancreatic fistula grade B or C showed no significant inter-group difference (9.5% vs. 9.5%). The median disease-free survival (34.5 vs. 17.3 months; P = 0.588) and overall survival (37.7 vs. 21.9 months; P = 0.171) were comparable between the groups. CONCLUSIONS: RDP is associated with longer operative time, a higher cost of surgery, and a higher likelihood of achieving R0 margins than LDP.

Data-driven and model-guided systematic framework for media development in CHO cell culture.

Proposed herein is a systematic media design framework that combines multivariate statistical approaches with in silico analysis of a genome-scale metabolic model of Chinese hamster ovary cell. The framework comprises sequential modules including cell culture and metabolite data collection, multivariate data analysis, in silico modeling and flux prediction, and knowledge-based identification of target media components. Two monoclonal antibody-producing cell lines under two different media conditions were used to demonstrate the applicability of the framework. First, the cell culture and metabolite profiles from all conditions were generated, and then statistically and mechanistically analyzed to explore combinatorial effects of cell line and media on intracellular metabolism. As a result, we found a metabolic bottleneck via a redox imbalance in the TCA cycle in the poorest growth condition, plausibly due to inefficient coenzyme q10-q10h2 recycling. Subsequent in silico simulation allowed us to suggest q10 supplementation to debottleneck the imbalance for the enhanced cellular energy state and TCA cycle activity. Finally, experimental validation was successfully conducted by adding q10 in the media, resulting in increased cell growth. Taken together, the proposed framework rationally identified target nutrients for cell line-specific media design and reformulation, which could greatly improve cell culture performance.

Combined multivariate statistical and flux balance analyses uncover media bottlenecks to the growth and productivity of Chinese hamster ovary cell cultures.

Chinese hamster ovary (CHO) cells are widely used for producing recombinant proteins. To enhance their productivity and product quality, media reformulation has been a key strategy, albeit with several technical challenges, due to the myriad of complex molecular mechanisms underlying media effects on culture performance. Thus, it is imperative to characterize metabolic bottlenecks under various media conditions systematically. To do so, we combined partial least square regression (PLS-R) with the flux balance analysis of a genome-scale metabolic model to elucidate the physiological states and metabolic behaviors of human alpha-1 antitrypsin producing CHO-DG44 cells grown in one commercial and another two in-house media under development. At the onset, PLS-R was used to identify metabolite exchanges that were correlated to specific growth and productivity. Then, by comparing metabolic states described by resultant flux distributions under two of the media conditions, we found suboptimal level of four nutrients and two metabolic wastes, which plausibly hindered cellular growth and productivity; mechanistically, lactate and ammonia recycling were modulated by glutamine and asparagine metabolisms in the media conditions, and also by hitherto unsuspected folate and choline supplements. Our work demonstrated how multivariate statistical analysis can be synergistically combined with metabolic modeling to uncover the mechanistic elements underlying differing media performance. It thus paved the way for the systematic identification of nutrient targets for medium reformulation to enhance recombinant protein production in CHO cells.

Tumor habitat analysis by magnetic resonance imaging distinguishes tumor progression from radiation necrosis in brain metastases after stereotactic radiosurgery.

OBJECTIVES: The identification of viable tumor after stereotactic radiosurgery (SRS) is important for future targeted therapy. This study aimed to determine whether tumor habitat on structural and physiologic MRI can distinguish viable tumor from radiation necrosis of brain metastases after SRS. METHOD: Multiparametric contrast-enhanced T1- and T2-weighted imaging, apparent diffusion coefficient (ADC), and cerebral blood volume (CBV) were obtained from 52 patients with 69 metastases, showing enlarging enhancing masses after SRS. Voxel-wise clustering identified three structural MRI habitats (enhancing, solid low-enhancing, and nonviable) and three physiologic MRI habitats (hypervascular cellular, hypovascular cellular, and nonviable). Habitat-based predictors for viable tumor or radiation necrosis were identified by logistic regression. Performance was validated using the area under the curve (AUC) of the receiver operating characteristics curve in an independent dataset with 24 patients. RESULTS: None of the physiologic MRI habitats was indicative of viable tumor. Viable tumor was predicted by a high-volume fraction of solid low-enhancing habitat (low T2-weighted and low CE-T1-weighted values; odds ratio [OR] 1.74, p <.001) and a low-volume fraction of nonviable tissue habitat (high T2-weighted and low CE-T1-weighted values; OR 0.55, p <.001). Combined structural MRI habitats yielded good discriminatory ability in both development (AUC 0.85, 95% confidence interval [CI]: 0.77-0.94) and validation sets (AUC 0.86, 95% CI:0.70-0.99), outperforming single ADC (AUC 0.64) and CBV (AUC 0.58) values. The site of progression matched with the solid low-enhancing habitat (72%, 8/11). CONCLUSION: Solid low-enhancing and nonviable tissue habitats on structural MRI can help to localize viable tumor in patients with brain metastases after SRS. KEY POINTS: • Structural MRI habitats helped to differentiate viable tumor from radiation necrosis. • Solid low-enhancing habitat was most helpful to find viable tumor. • Providing spatial information, the site of progression matched with solid low-enhancing habitat.

Diffuse glioma, not otherwise specified: imaging-based risk stratification achieves histomolecular-level prognostication.

OBJECTIVES: To determine whether imaging-based risk stratification enables prognostication in diffuse glioma, NOS (not otherwise specified). METHODS: Data from 220 patients classified as diffuse glioma, NOS, between January 2011 and December 2020 were retrospectively included. Two neuroradiologists analyzed pre-surgical CT and MRI to assign gliomas to the three imaging-based risk types considering well-known imaging phenotypes (e.g., T2/FLAIR mismatch). According to the 2021 World Health Organization classification, the three risk types included (1) low-risk, expecting oligodendroglioma, isocitrate dehydrogenase (IDH)-mutant, and 1p/19q-codeleted; (2) intermediate-risk, expecting astrocytoma, IDH-mutant; and (3) high-risk, expecting glioblastoma, IDH-wildtype. Progression-free survival (PFS) and overall survival (OS) were estimated for each risk type. Time-dependent receiver operating characteristic analysis using 10-fold cross-validation with 100-fold bootstrapping was used to compare the performance of an imaging-based survival model with that of a historical molecular-based survival model published in 2015, created using The Cancer Genome Archive data. RESULTS: Prognostication according to the three imaging-based risk types was achieved for both PFS and OS (log-rank test, p < 0.001). The imaging-based survival model showed high prognostic value, with areas under the curves (AUCs) of 0.772 and 0.650 for 1-year PFS and OS, respectively, similar to the historical molecular-based survival model (AUC = 0.74 for PFS and 0.87 for OS). The imaging-based survival model achieved high long-term performance in both 3-year PFS (AUC = 0.806) and 5-year OS (AUC = 0.812). CONCLUSION: Imaging-based risk stratification achieved histomolecular-level prognostication in diffuse glioma, NOS, and could aid in guiding patient referral for insufficient or unsuccessful molecular diagnosis. KEY POINTS: • Three imaging-based risk types enable distinct prognostication in diffuse glioma, NOS (not otherwise specified). • The imaging-based survival model achieved similar prognostic performance as a historical molecular-based survival model. • For long-term prognostication of 3 and 5 years, the imaging-based survival model showed high performance.

Identification of essential element determining fruit-specific transcriptional activity in the tomato HISTIDINE DECARBOXYLASE A gene promoter.

KEY MESSAGE: In SlHDC-A promoter, SlHDC-A core-ES is an essential region for fruit-specific expression and interacts with GATA, HSF and AP1. Triplication of essential region was proposed as a minimal fruit-specific promoter. In plant biotechnology, fruit-specific promoter is an important tool for the improvement and utilization of tomato fruit. To expand our understanding on fruit-specific expression, it is necessary to determine the promoter region involved in fruit-specific transcriptional activity and transcriptional regulations of the promoter. In previous study, we isolated a fruit-specific SlHDC-A core promoter specifically expressed during tomato ripening stages. In this study, we identified SlHDC-A promoter region (SlHDC-A core-ES) that is essential for fruit-specific expression of the SlHDC-A. To understand the molecular mechanisms of fruit-specific expression of the SlHDC-A promoter, we first identified the putative transcription factor binding elements in the SlHDC-A core promoter region and corresponding putative transcription factors which are highly expressed during fruit maturation. Yeast one hybrid analysis confirmed that GATA, HSF, and AP1 interact with the SlHDC-A core-ES promoter region. Further transactivation analysis revealed that expression of the three transcription factors significantly activated expression of a reporter gene driven by SlHDC-A core-ES promoter. These results suggest that GATA, HSF, and AP1 are involved in the fruit-specific expression of SlHDC-A promoter. Furthermore, the synthetic promoter composed of three tandem repeats of SlHDC-A core-ES showed relatively higher activity than the constitutive 35S promoter in the transgenic tomato fruits at the orange stage. Taken together, we propose a new synthetic promoter that is specifically expressed during fruit ripening stage.

Controversial benefit of 5-fluorouracil/leucovorin-based adjuvant chemotherapy for ampullary cancer: a propensity score-matched analysis.

BACKGROUND: Although surgery is the primary treatment for ampullary cancer (AC), the benefit of adjuvant chemotherapy (CTx) has not yet been confirmed. METHODS: AC patients who were administered 5-fluorouracil(FU)/leucovorin(LV)-based CTx after curative intent surgery between 2011 and 2019 were included. Prognosis was compared between the observation (OB) and CTx groups after propensity score matching (PSM) using perioperative variables to control differences in patient characteristics. RESULTS: Before PSM, of 475 patients, those in the CTx group (n = 281) had worse 5-year overall survival (OS) (82.1% vs. 78.5%, p = 0.017) and worse 5-year recurrence-free survival (RFS) (54.9% vs. 75.7%, p < 0.001) than those in the OB group (n = 194). In addition, the CTx group had a higher rate of poor prognostic factors such as a high T stage (p < 0.001), node metastasis (p < 0.001), and poor differentiation (p < 0.001). After PSM, perioperative outcomes were comparable. In addition, there were no significant differences in OS (hazard ratio [HR], 1.085; 95% confidence interval [CI], 0.688-1.710; p = 0.726) or RFS (HR, 0.883; 95% CI, 0.613 1.272; p = 0.505) between the CTx (n = 123) and OB (n = 123) groups even after stratification by TNM stage. Intestinal subtype showed better 5-year OS (83.7% vs 33.2%, p = 0.015) and RFS (46.5% vs 24.9%, p = 0.035) rate compared with pancreatobiliary/mixed subtype. CONCLUSION: Patients who received adjuvant chemotherapy based on 5-FU/LV showed comparable oncologic outcomes to patients in the OB group even after stratification by tumor stage. The patients with intestinal subtype showed oncologic benefit for adjuvant 5-FU/LV CTx compared with pancreatobiliary or mixed subtypes.

Treatment outcome of continuation of intravenous amikacin for Mycobacterium abscessus pulmonary disease with a persistent culture positivity after the treatment initiation.

INTRODUCTION: Whether prolonged intravenous amikacin treatment would lead to better treatment results in patients with Mycobacterium abscessus subspecies abscessus (M. abscessus) pulmonary disease (PD) is unknown. We investigated the efficacy of continued amikacin treatment for the microbiological outcome of M. abscessus PD patients with persistent culture positivity after treatment initiation. METHODS: We retrospectively evaluated 62 patients with M. abscessus PD who were treated with intravenous amikacin and beta-lactams along with a macrolide-based regimen at 3 tertiary referral centers in South Korea. The intravenous antibiotic treatment duration was determined by the attending physician. RESULTS: The median treatment durations with amikacin and beta-lactam in the 62 patients were 25.1 and 8.2 weeks, respectively. The overall microbiological cure rate was 29.0%. Among the 62 patients, 44 showed persistent culture positivity at 8 weeks after treatment with an amikacin-containing multidrug regimen. The median parenteral amikacin treatment duration after 8 weeks in these patients was 18.0 weeks. The conditional probability of microbiological cure with continuation of the amikacin-containing regimen in these patients was 18.2% (95% confidence interval 8.2-32.7). Additionally, the conditional probability of microbiological cure in the 34 patients with persistent culture positivity at 12 weeks was 8.8% (95% confidence interval 1.9-23.7). After 16 weeks, the conditional probability of microbiological cure decreased further, reaching 0% at 28 weeks after treatment initiation. CONCLUSION: The continuation of intravenous amikacin therapy was usually not followed by culture conversion in M. abscessus PD patients with persistent sputum culture positivity after treatment initiation.